Cardiorenal Syndrome

Cardiorenal Syndrome

Adel E. Berbari • Giuseppe Mancia (Eds.)

Cardiorenal Syndrome Mechanisms, Risk and Treatment

123

Editors Adel E. Berbari Department of Internal Medicine American University of Beirut Medical Center Beirut, Lebanon Giuseppe Mancia Clinica Medica Department of Clinical Medicine and Prevention University of Milano-Bicocca San Gerardo Hospital Monza, Milan, Italy

ISBN 978-88-470-1462-6

e-ISBN 978-88-470-1463-3

DOI 10.1007/978-88-470-1463-3 Springer Milan Dordrecht Heidelberg London New York Library of Congress Control Number: 2010925384 © Springer-Verlag Italia 2010 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the Italian Copyright Law in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the Italian Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Product liability: The publishers cannot guarantee the accuracy of any information about dosage and application contained in this book. In every individual case the user must check such information by consulting the relevant literature. 9 8 7 6 5 4 3 2 1 Cover design: Simona Colombo, Milan, Italy Typesetting: Graphostudio, Milan, Italy Printing and binding: Arti Grafiche Nidasio, Assago (MI), Italy Printed in Italy Springer-Verlag Italia S.r.l. – Via Decembrio 28 – I-20137 Milan Springer is a part of Springer Science+Business Media (www.springer.com)

Preface

It has long been known that a close relationship exists between chronic kidney disease (CKD) and cardiovascular disease (CVD), which has led to the adoption of the terminology “cardiorenal syndrome”. In recent years, the relationship between CKD and CVD has been shown to be even closer because of the demonstration that renal function acts as a sensor of global (or total) CVD risk. It is thus now well documented that from the initial to the advanced stages of renal disease, the cardiovascular system is involved. Primary disorders of CKD are associated with an enhanced progression of CVD, even when renal function is only mildly impaired. A significant number of patients with CKD die of CVD complications before they progress to end-stage renal failure. This excessive CVD risk is attributed to a high burden of both conventional and kidney (uremia)-related factors as well as to a wide spectrum of clinicopathologic entities. Conversely, primary CV disorders can initiate and perpetuate functional renal impairment and progressive CKD. Overall, the presence of renal dysfunction is an ominous sign of poor outcome in patients who develop ischaemic syndromes or undergo any type of surgical intervention. Although a large number of clinical studies and reviews has addressed the cardiorenal syndrome, the editors deemed it appropriate to provide readers with a book that comprehensively addresses all the complex interactive aspects of the cardiorenal relationship, i.e. from pathophysiology to epidemiology, diagnosis and treatment. We believe that understanding the mechanisms linking CKD and CVD is essential also to have more clear perspectives on the future therapeutic approaches to this deadly association. We express our deep gratitude and warm appreciation to the experts who kindly contributed to the various chapters of this book. Beirut-Milan, June 2010

Adel E. Berbari Giuseppe Mancia

v

Contents

Section I

01

02

Chronic Kidney Disease and Cardiovascular Disease Interrelationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Links between Chronic Kidney Disease and Cardiovascular Disease: A Bidirectional Relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adel E. Berbari Cardiorenal versus Renocardiac Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . Mohammad Sarraf, Amirali Masoumi, Robert W. Schrier

Section II

Crosstalk between the Cardiovascular System and the Kidney . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

03

Non-Pressure-Related Deleterious Effects of Excessive Dietary Sodium . . Albert Mimran

04

Regulation of Vascular and Renal Cells by Common Mediators in Health and Disease: Role of the Renin–Angiotensin System in the Pathophysiology of Hypertension and Cardiovascular Disease . . . . . Marta Ruiz-Ortega, Raquel Rodrigues-Díez, Sandra Rayego, Raul R. Rodrigues-Díez, Carolina Lavoz, Esther Civantos, Gisselle Carvajal, Sergio Mezzano, Alberto Ortiz, Jesus Egido

Section III

05

Chronic Kidney Disease as a Risk for Cardiovascular Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cardiorenal Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Josè A. García-Donaire, Luis M. Ruilope

1

3

15

35 37

49

65 67

vii

Contents

viii

06

07

Definition and Classification of Stages of Chronic Kidney Disease: Screening for Chronic Kidney Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tariq Shafi, Joseph Coresh

81

Cardiovascular Disease Risk Factors in Chronic Kidney Disease: Traditional, Nontraditional, and Uremia-related Threats . . . . . . . . . . . . . . . Juan J. Carrero, Peter Stenvinkel

91

08

Increased Levels of Urinary Albumin: A Cardiovascular Risk Factor and a Target for Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Dick de Zeeuw, Hiddo J. Lambers Heerspink

09

Microalbuminuria and Kidney Disease: An Evidence-based Perspective . . 117 Rigas G. Kalaitzidis, Pranav Dalal, George L. Bakris

10

Cardiometabolic Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Manjula Kurella Tamura, Tara I. Chang

11

Diabetes Mellitus: Is the Presence of Nephropathy Important as a Cardiovascular Risk Factor for Cardiorenal Syndrome? . . . . . . . . . . . . . . . 145 Hussein H. Karnib, Fuad N. Ziyadeh

Section IV

Spectrum of Cardiovascular Disease in Chronic Kidney Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

12

Cardiovascular Disease: Coronary Artery Disease and Coronary Artery Calcification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Srinivasan Beddhu

13

Cardiomyopathy in Chronic Kidney Disease and in End-stage Renal Disease 175 Frank A. Benedetto, Francesco Perticone, Carmine Zoccali

14

Pathophysiological Mechanisms and Prognostic Significance of Renal Functional Impairment in Cardiac Patients . . . . . . . . . . . . . . . . . . . . . . . . . 189 Massimo Volpe, Marco Testa

15

Stroke. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Mario F. Rubin, Raymond R. Townsend

Section V 16

Mechanisms of Cardiovascular Complications . . . . . . . . . . . . . . . . 217

Uremic Toxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Griet Glorieux, Eva Schepers, Raymond Vanholder

Contents

ix

17

Endothelial Dysfunction, Nitric Oxide Bioavailability, and Asymmetric Dimethyl Arginine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Carmine Zoccali

18

Pathophysiologic Link between Atherosclerosis and Nephrosclerosis . . . . . 245 Elena Kaschina, Thomas Unger

19

Aortic Stiffness, Kidney Disease, and Renal Transplantation . . . . . . . . . . . 255 Sola A. Bahous, Michael Delahousse, Michel E. Safar

20

Disturbed Calcium–Phosphorus Metabolism/Arterial Calcifications: Consequences on Cardiovascular Function and Clinical Outcome . . . . . . . 269 Gérard M. London, Bruno Pannier, Sylvain J. Marchais

21

Role of Neurohormonal Activation in the Pathogenesis of Cardiovascular Complications in Chronic Kidney Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 Andrea Stella, Giovanna Castoldi

22

Impaired Autonomic Blood Pressure and Blood Volume Control in Chronic Renal Failure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 Guido Grassi, Raffaella Dell’Oro, Fosca Quarti-Trevano, Giuseppe Mancia

23

Role of Novel Biomarkers in Chronic Kidney Disease: Urotensin II . . . . . . 299 Francesca Mallamaci, Daniela Leonardis, Maria Borrajo

24

Role of Novel Biomarkers in Chronic Kidney Disease: Renalase . . . . . . . . 309 Gary V. Desir

Section VI

Regression/Progression of Chronic Kidney Disease . . . . . . . . . . . . 317

25

Diabetic Kidney Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 Josep Redon

26

Nondiabetic Kidney Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 Paolo Cravedi, Piero Ruggenenti, Giuseppe Remuzzi

Section VII 27

Therapeutic Modalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357

Approaches in the Management of Patients with Chronic Kidney Disease and Cardiovascular Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359 Eberhard Ritz

x

28

Contents

Trends in the Management of Cardiac Patients with Renal Functional Impairment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 Edward A. Ross, Amir Kazory

Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387

List of Contributors

Sola A. Bahous Division of Nephrology and Hypertension Centre Hospitalier du Nord Lebanese American University School of Medicine Byblos, Lebanon George L. Bakris Department of Medicine - Hypertensive Diseases Unit The University of Chicago Pritzker School of Medicine Chicago, IL, USA Srinivasan Beddhu Department of Medicine University of Utah School of Medicine Salt Lake City, UT, USA Frank A. Benedetto Cardiology Clinical Rehabilitation Unit A.O. “Bianchi-Melacrino-Morelli” Reggio Calabria, Italy Adel E. Berbari Department of Internal Medicine American University of Beirut Medical Center Beirut, Lebanon

Maria Borrajo Nephrology Unit Complexo Hospitalario de Ourense (CHOU) Ourense, Spain Juan J. Carrero Division of Renal Medicine Department of Clinical Science, Intervention and Technology Karolinska Institutet Stockholm, Sweden Gisselle Carvajal Universidad Austral Valdivia, Chile Giovanna Castoldi Kidney Unit San Gerardo Hospital Monza, Milan, Italy and Department of Clinical Medicine and Prevention University of Milano-Bicocca Monza, Milan, Italy Tara I. Chang Division of Nephrology Stanford University School of Medicine Palo Alto, CA, USA

xi


xii

Esther Civantos Cellular Biology in Renal Diseases Laboratory Universidad Autónoma de Madrid Madrid, Spain

Jesus Egido Renal Research Laboratory Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid, Spain

Joseph Coresh Department of Epidemiology, Biostatistics and Medicine Johns Hopkins University Baltimore, MD, USA

Josè A. García-Donaire Hypertension Unit Hospital 12 de Octubre Madrid, Spain

Paolo Cravedi Mario Negri Institute for Pharmacological Research Bergamo, Italy Pranav Dalal Department of Medicine Mount Sinai Hospital Chicago, IL, USA Dick de Zeeuw Department of Clinical Pharmacology University Medical Center Groningen, Netherlands Michael Delahousse Department of Nephrology Foch Hospital Suresnes, France Raffaella Dell’Oro Clinica Medica Department of Clinical Medicine and Prevention University of Milano-Bicocca San Gerardo Hospital Monza, Milan, Italy Gary V. Desir Department of Internal Medicine VACHS, Yale School of Medicine New Haven, CT, USA

Griet Glorieux Nephrology Unit Department of Internal Medicine University Hospital Gent Gent, Belgium Guido Grassi Clinica Medica Department of Clinical Medicine and Prevention University of Milano-Bicocca San Gerardo Hospital Monza, Milan, Italy Rigas G. Kalaitzidis Department of Medicine Endocrinology/Hypertension Section University of Chicago School of Medicine Chicago, IL, USA Hussein H. Karnib Department of Physiology/Internal Medicine American University of Beirut Medical Center Beirut, Lebanon Elena Kaschina Center for Cardiovascular Research/CCR Institute of Pharmacology Charité-Universitätsmedizin Berlin, Germany


Amir Kazory Division of Nephrology, Hypertension and Transplantation University of Florida Gainesville, FL, USA Manjula Kurella Tamura Division of Nephrology Stanford University School of Medicine and VA Palo Alto Health Care System Geriatrics Research and Education Clinical Center Palo Alto, CA, USA Hiddo J. Lambers Heerspink Department of Clinical Pharmacology University Medical Center Groningen, Netherlands Carolina Lavoz Cellular Biology in Renal Diseases Laboratory Universidad Autónoma de Madrid Madrid, Spain Daniela Leonardis Nephrology, Hypertension and Renal Transplantation Unit and CNR-IBIM A.O. “Bianchi-Melacrino-Morelli” Reggio Calabria, Italy

xiii

Giuseppe Mancia Clinica Medica Department of Clinical Medicine and Prevention University of Milano-Bicocca San Gerardo Hospital Monza, Milan, Italy Sylvain J. Marchais Service d’Hémodialyse Hôpital F.H. Manhès Fleury-Mérogis, France Amirali Masoumi Department of Medicine University of Colorado Denver Aurora, CO, USA Sergio Mezzano Universidad Austral Valdivia, Chile Albert Mimran Department of Internal Medicine Centre Hospitalier Universitaire Moltpellier, France Alberto Ortiz Diasysis Unit Fundación Jiménez Díaz Madrid, Spain

Gérard M. London Service d’Hémodialyse Hôpital F.H. Manhès Fleury-Mérogis, France

Bruno Pannier Service d’Hémodialyse Hôpital F.H. Manhès Fleury-Mérogis, France

Francesca Mallamaci Nephrology, Hypertension and Renal Transplantation Unit and CNR-IBIM A.O. “Bianchi-Melacrino-Morelli” Reggio Calabria, Italy

Francesco Perticone Department of Experimental and Clinical Medicine G. Salvatore University Magna Grecia Catanzaro, Italy


xiv

Fosca Quarti-Trevano Clinica Medica Department of Clinical Medicine and Prevention University of Milano-Bicocca San Gerardo Hospital Monza, Milan, Italy Sandra Rayego Cellular Biology in Renal Diseases Laboratory Universidad Autónoma de Madrid Madrid, Spain Josep Redon Internal Medicine – Hypertension Clinic Hospital Clinico University of Valencia Valencia, Spain Giuseppe Remuzzi Mario Negri Institute for Pharmacological Research, Bergamo and Unit of Nephrology and Dialysis A.O. Ospedali Riuniti Bergamo, Italy Eberhard Ritz Nierenzentrum/Department of Internal Medicine Ruperto Carola University Heidelberg, Germany Raquel Rodrigues-Díez Cellular Biology in Renal Diseases Laboratory Universidad Autónoma de Madrid Madrid, Spain Raul R. Rodrigues-Díez Cellular Biology in Renal Diseases Laboratory Universidad Autónoma de Madrid Madrid, Spain

Edward A. Ross Division of Nephrology, Hypertension and Transplantation University of Florida Gainesville, FL, USA Mario F. Rubin Renal Unit Department of Medicine Massachussets General Hospital Boston, MA, USA Piero Ruggenenti Mario Negri Institute for Pharmacological Research, Bergamo and Unit of Nephrology and Dialysis A.O. Ospedali Riuniti Bergamo, Italy Luis M. Ruilope Hypertension Unit Hospital 12 de Octubre Madrid, Spain Marta Ruiz-Ortega Cellular Biology in Renal Diseases Laboratory Universidad Autónoma de Madrid Madrid, Spain Michel E. Safar Université Paris Descartes Assistance Publique-Hôpitaux de Paris Hôtel-Dieu Centre de Diagnostic et de Thérapeutique Paris, France Mohammad Sarraf Department of Medicine University of Colorado Denver Aurora, CO, USA


Eva Schepers Nephrology Unit Department of Internal Medicine University Hospital Gent Gent, Belgium Robert W. Schrier Division of Renal Diseases and Hypertension University of Colorado Denver Aurora, CO, USA Tariq Shafi Department of Medicine/Nephrology Johns Hopkins University School of Medicine Baltimore, MD, USA Andrea Stella Kidney Unit San Gerardo Hospital Monza, Milan, Italy and Department of Clinical Medicine and Prevention University of Milano-Bicocca Monza, Milan, Italy Peter Stenvinkel Division of Renal Medicine Department of Clinical Science, Intervention and Technology Karolinska Institutet Stockholm, Sweden Marco Testa Division of Cardiology II Faculty of Medicine University of Rome “La Sapienza” Sant’Andrea Hospital Rome, Italy

xv

Raymond R. Townsend Department of Medicine University of Pennsylvania Philadelphia, PA, USA Thomas Unger Center for Cardiovascular Research/CCR Institute of Pharmacology Charité-Universitätsmedizin Berlin, Germany Raymond Vanholder Nephrology Unit Department of Internal Medicine University Hospital Gent Gent University, Belgium Massimo Volpe Division of Cardiology II Faculty of Medicine University of Rome “La Sapienza” Sant’Andrea Hospital Rome, Italy Fuad N. Ziyadeh Department of Internal Medicine/Biochemistry American University of Beirut Medical Center Beirut, Lebanon Carmine Zoccali Nephrology, Hypertension and Renal Transplantation Unit and CNR-IBIM A.O. Ospedali Riuniti Reggio Calabria, Italy

Section I

Chronic Kidney Disease and Cardiovascular Disease Interrelationships

Links between Chronic Kidney Disease and Cardiovascular Disease: A Bidirectional Relationship

1

A.E. Berbari

Abstract A strong relationship between chronic kidney disease (CKD) and accelerated cardiovascular disease, defined as the cardiorenal syndrome, is well documented, whether the initial event is in the kidney or in the heart. In the kidney context, mechanisms that link CKD and cardiovascular disease (CVD) involve both conventional and CKD (uremia)-related CVD risk factors. Several pathophysiologic processes responsible for the accelerated CVD spectrum in the CKD population include accelerated calcific occlusive atheromatous disease, diffuse nonocclusive medial-wall calcification, endothelial dysfunction, and uremic cardiomyopathy. In the heart context, disturbed CV dynamics and activation of neurohormonal and inflammatory factors are involved in the initiation of renal functional impairment and progressive kidney disease. The aim of this chapter is to present an overview of various aspects of cardiorenal association and to pinpoint features that are specific to each clinical entity, whether the initial insult is renal or cardiac. A detailed discussion of the various aspects of cardiorenal association are well covered in the following chapters. Keywords: Cardiorenal syndrome • Conventional and CKD-related risk factors • Calcific intimal atherosclerosis • Arteriosclerosis • Myocardial dysfunction

1.1 Introduction Several epidemiologic observations and clinical studies have documented a strong relationship between chronic kidney disease (CKD) and accelerated cardiovascular disease (CVD) morbidity and mortality [1]. This relationship exists whether the initial event is renal parenchymal disease or cardiac disease. Whereas death rates from coronary artery disease fell by 40% in the last decade as a result of control of CVD risk factors

A.E. Berbari () Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon Cardiorenal Syndrome. Adel E. Berbari, Giuseppe Mancia (Eds.) © Springer-Verlag Italia 2010

3

4

1

A. E. Berbari

and therapeutic interventions, no such trend has occurred in patients with CKD or endstage renal disease (ESRD) [2]. A significant number of patients with CKD die of cardiovascular complications before they progress to end-stage renal failure (ESRF) [3]. On the other hand, renal dysfunction in patients with primary cardiac disease portends a significantly enhanced risk of morbidity and mortality from CVD [4, 5]. An aging population and increasing incidence of hypertension, diabetes mellitus, obesity, and other comorbid factors are associated with an increasing incidence of cardiorenal disorders [1].

1.2 Definition Cardiorenal syndrome, a term increasingly used to describe the interaction between CKD and CVD, can be defined as a clinicopathologic disorder in which a primary insult in the kidney or in the heart initiates a series of secondary functional and morphologic responses in the other organ [6]. Some authors prefer to use different terms to denote whether the primary insult that initiates the secondary responses is in the kidney (renocardiac syndrome) or in the heart (cardiorenal syndrome) [7]. In this chapter, the term cardiorenal syndrome is retained to describe the cardiorenal association whether the initial insult is in the kidney or in the heart.

1.3 Chronic Kidney Disease as a Promoter of Cardiovascular Disease CKD is associated with accelerated progression of CVD, even when renal function is mildly impaired. The higher risk for CVD has been reported all along the continuum of CKD – from increased urinary albumin excretion to ESRD. About 50% of CKD patients die of cardiovascular complications before they progress to ESRD [8]. Mortality from CVD is 10–20 times higher in predialysis patients and in those undergoing dialysis replacement treatment compared with age- and sex-matched healthy individuals with no evidence of CKD [9]. Furthermore, CKD patients who develop acute ischemic events or undergo percutaneous coronary interventions or coronary bypass surgery have a much poorer outcome than their counterparts with a normal renal function [4, 5].

1.3.1 Epidemiology CKD is emerging as a global health problem. It is a major risk for accelerated CVD and progression to ESRF. The prevalence of CKD is surprisingly high in the general

1 Links between Chronic Kidney Disease and Cardiovascular Disease: A Bidirectional Relationship

5

population. In the USA, The Third National and Nutrition Survey Examination (NHANES III) reported a prevalence of 11% in the adult population [10, 11]. Rates appear to be similar in Europe but higher in other populations, such as in Asia and Australia. Furthermore, in patients with comorbid conditions such as hypertension, diabetes mellitus, and heart disease, the incidence of renal dysfunction is higher than in the general population [11]. An accurate estimation of renal function is fundamental for detecting CKD. The diagnosis of renal dysfunction is based on one or more of the following criteria: (1) elevated serum creatinine level; (2) decreased glomerular filtration rate (GFR); (3) increased urinary albumin excretion [11, 12]. GFR can be measured directly from serum creatinine and urinary creatinine excretion obtained from 24-h urine collection, estimated by the abbreviated Modification of Diet in Renal Disease (MDRD) equation, or by the Cockroft-Gault formula. The latter is valid for GFR >60 ml/min/1.73m2, as it tends to overestimate renal function in advanced stages of renal impairment as well as in overweight and obese individuals. Based on the estimated GFR (eGFR) by the MDRD equation, CKD is classified into five (I–V) stages; eGFR 50% of the normal GFR value of 125 ml/min.1.73m2 in young men and women. This level of GFR is associated with the onset of laboratory abnormalities characteristic of kidney failure, including increased prevalence and severity of several CVD risk factors. GFR values of 59–30 and 29–15 ml/min/1.73m2 define CKD stages III and IV, respectively. GFR values 300 mg/day [12]. Only 25% of individuals with GFR 60ml/min/1.73m2 versus those with GFR 130 μmol/l or ≥1.47 mg/dl) and normal or mild uncomplicated hypertension, an inverse relationship between arterial stiffness and renal function was noted [24]. Serum creatinine concentration was the only predictor of the increased arterial stiffness. It can be postulated that with declining renal function, changes in serum phosphate concentrations – although still within the conventional reference range – may trigger vascular calcification and cause increased arterial stiffness. Interestingly, dose-dependent associations between serum phosphate concentrations, even within the conventional reference range, and CVD outcomes were reported in individuals free of CVD and CKD [25]. In contrast, other studies showed no substantive difference in arterial stiffness between individuals with and without mild to moderate CKD; microalbuminuria was the only index that correlated with arterial stiffness [26]. Diffuse nonocclusive medial calcification and increased arterial stiffness are the more dominant forms of vascular pathology in adolescents and young adults with CKD. These morphologic changes are associated with systolic hypertension, wide pulse pressure, LVH, coronary hypoperfusion, further renal damage, congestive heart failure (CHF), and sudden death [27] (Fig. 1.2).

1.3.2.3 Endothelial Dysfunction Impaired endothelial function occurs early in renal disease and has been attributed to a number of potential causes [15]: 1. Reduced clearance of endothelial nitric oxide synthase (e-NOS) inhibitor asymmetric dimethyl arginine (ADMA), which leads to reduced bioavailability of endothelial nitric oxide 2. Activation of angiotensin II, which induces oxidative stress 3. High levels of homocysteine 4. Chronic inflammation 5. Dyslipidemia 6. Endothelial progenitor-cell deficiency [28] Endothelial dysfunction contributes significantly to the initiation and progression

1 Links between Chronic Kidney Disease and Cardiovascular Disease: A Bidirectional Relationship

9

of CVD in CKD. It exacerbates arterial-luminal narrowing and arterial-wall stiffening by allowing development of intima–media thickening, medial hypertrophy, and calcification [15].

1.3.2.4 Uremia-Related CVD A significant number of uremic patients with ESRF manifest: (1) symptoms of myocardial ischemia with no evidence of significant coronary artery disease by coronary angiography; (2) CHF generally resistant to therapy. These clinical conditions result from functional and morphologic features specific to the uremic state [11, 29, 30]. With worsening renal function and onset of ESRF, uremic patients characteristically have hypertension, anemia, hyperactive circulation due to arteriovenous fistulae, increased arterial stiffness, and LVH and cardiac dilatation as a result of pressure and volume overload and abnormal metabolic profile [30]. The structure of the myocardium itself also is altered in a manner that is characterized by intramyocardial coronary artery thickening, reduced myocardial capillary density, and increased interstitial myocardial fibrosis [30]. All these factors cause a cardiomyopathy which is specific to the uremic state and is known as uremic cardiomyopathy. In these patients, clinical manifestations include heart failure, ischemic heart disease even in the absence of coronary artery disease, arrhythmias, and sudden cardiac-related death.

1.3.3 Course of CVD in CKD It is well established that terminal stages of CKD are associated with markedly elevated CVD burden. CVD morbidity and mortality are 100 times higher in ESRF patients compared with age- and gender-matched individuals with no kidney disease [9, 12]. CKD is a well recognized risk factor for accelerated CVD. There is a strong, continuous correlation between increased risk for CVD events and impaired renal function. The relationship between CKD and CVD, however, is not linear but exponential. The risk begins in the early stages of renal impairment and increases continuously to 20–30 times higher than in the general population as renal damage progresses to ESRD. This risk is evident at an eGFR of 1g/day, the

8 Increased Levels of Urinary Albumin: A Cardiovascular Risk Factor and a Target for Treatment

107

majority of that protein is usually albumin. Thus, the choice of measuring total protein versus albumin becomes arbitrary. However, in the event of lower total protein levels, the relative contribution of urinary proteins other than albumin increases, and the specific measurement of albuminuria is warranted. In clinical practice, albuminuria is often chosen to measure renal disease and CVD risk, particularly in diabetic patients and in patients with essential hypertension. In nondiabetic patients, proteinuria is usually measured. Determining which protein is related to renal or CVD risk is as yet unknown. Albumin may qualify, as its size and charge is such that it will not easily pass the intact glomerular or vascular barrier. In the event of decreased barrier function, albumin will pass both the glomerular and vascular barrier. This might explain why albuminuria predicts both CVD and renal disease risk. Thus, to date, for CVD and renal disease risk stratification and for therapy monitoring, albumin appears to be the molecule of interest. However, it could also be that another plasma protein (cofiltered with albumin) is better related to renal and CV damage or damage prediction when one studies this in more detail [2].

8.2.1.2 Measurement Technique Another ongoing important debate is which technique we should use to measure urinary albumin. Most common laboratory techniques use antibodies that bind to the albumin molecule (or its fragments) and subsequently detect the amount of formed complexes. It is important to realize that the antibodies used are raised against albumin derived from plasma. Whether this is an appropriate antibody is questionable, as urinary albumin may not have the same characteristics for antibody binding as plasma albumin due to the distinctly different environment of plasma and urine passing through the renal filter and tubules. Indeed, when one measures urinary albumin with a nonimmunological technique such as high-performance liquid chromatography (HPLC), one detects more albumin compared with the antibody techniques. This opens up a whole new area of research. Not only is it important to truly quantify albumin but to verify whether and to what extent a new measurement technique alters the predictive power of this parameter on outcome [3].

8.2.1.3 Urine Collection To measure urinary albumin, one needs to collect the urine. Traditionally, 24-h urinary collection is taken. This forces the patient to carry urine collection containers. Other, more practical, collection strategies involve a spot urine sample (the patient produces a urine sample at any time of the day) or a first-morning void (the patient collects the first morning urine after awaking). In case of a 24-h collection, one can

D. de Zeeuw, H.J. Lambers Heerspink

108

8

calculate the amount of albumin excretion per time. This allows standardized monitoring between patients and within a patient. The problem with urine portion collection techniques is that they can only quantify urinary albumin concentration, which could be problematic for standardization when the individual/patient has varying urinary albumin concentration from day to day or within a day. This problem can be overcome by using urinary creatinine excretion as a reference and dividing urinary albumin by urinary creatinine. The use of the albumin/creatinine ratio filters out the possible urinary concentration differences. However, the need for measuring creatinine introduces another bias. In addition to the measurement error of creatinine, the amount of creatinine may differ within (diurnal variation) and between (muscle mass) individuals. As all three collection (and correction) techniques are associated with different cutoff figures of normoalbuminuria, microalbuminuria, and macroalbuminuria (Table 8.1), the wide-spread clinical use of albumin as a risk marker is complicated. Standardization and guidelines are therefore desperately needed. Even if one collects accurately, day to day variation in albumin excretion appears to be present. Whether this is physiological or pathophysiological or still due to collection or even measurement errors remains hard to resolve. To avoid this variability as much as possible, multiple consecutive collections (three times) may help, as well as repeating collections three times with a week interval (modified from [1]). The decision regarding the choice of collection or correction technique clearly depends on the goal. Obviously, the technique used should most accurately measure the true amount of albumin. In addition, the risk prediction properties of albuminuria should not be compromised by the technique used. An early and easy collection technique is preferable for screening purposes, whereas more accuracy and precision is required in for diagnoses. Several studies have shown that spot sampling is inferior to 24-h collection for albuminuria quantification [4]. Collection of a first-morning

Table 8.1 Definitions and threshold levels for urinary albumin according to the Kidney Disease: Improving Global Outcomes (KDIGO) consensus [1] 24-hour urine collection, Albumin albumin excretion rate concentration (mg/day) (mg/L)

Spot morning urine sample, albumin to creatinine ratio mg/mmol 300


109

void, however, is an adequate technique and comparable to 24-h collection – both for albuminuria quantification and risk prediction [5]. Whether the creatinine correction (albumin/creatinine ratio) brings any added value over albumin concentration is questionable. For screening purposes, first-morning-void albumin concentration seems to be adequate. Whether creatinine correction is needed for monitoring and follow-up needs to be further studied.

8.2.1.4 Fresh or Frozen Sample? Urine samples for albumin measurement should be fresh. There is no reason in clinical practice to store urine, as the results need to be directly available. However, for those involved in research studies with follow-up measurements of albuminuria, or those involved in large epidemiological studies, the need for urine storage may be present. In general, urine does not require special treatment after collection and can withstand many hours at room temperature without affecting urinary albumin measurement. However, freezing, particularly at –20°C, introduces clear and variable changes in the level of albumin measured in the sample. Changes increase with longer storage, which affects predictive properties of albuminuria in CVD risk [6]. The increased variability in urinary albumin observed during frozen storage may be due to factors such as urinary pH [7]. Correcting urinary pH or freezing at –70°C remains the best way to store urine samples if needed.

8.3 Epidemiology Albumin excretion varies within the population. The majority of people have low levels of albumin excretion, some even below the detection limit. Around 10% have increased albumin excretion in the microalbuminuric range, and only a limited number of individuals have macroalbuminuria (proteinuria). The prevalence of microalbuminuria appears to be quite similar throughout the Western world. To date, studies have been carried out in Europe (Netherlands, Norway), Australia, and the USA, showing roughly the same distribution [8]. In the general population, individuals with diseases such as hypertension or diabetes have an increased prevalence of microalbuminuria (20%), although the numbers on this vary considerably between studies. However, even among individuals in the healthy (nondiabetic, nonhypertensive) general population, microalbuminuria is highly prevalent and is still predictive for cardiovascular outcome. Increased levels of urinary albumin cluster with other CVD risk factors, such as age, body weight, smoking, diabetes, and hypertension. Individuals with either one or a combination of such conditions show a higher prevalence of microalbuminuria or proteinuria. Incident microalbuminuria is also higher in these cases. The increased

110

8


prevalence and incidence suggests that microalbuminuria may be the consequence of these other risk factors. However, microalbuminuria can be found in children and even babies [8]. This may suggest that microalbuminuria reflects early presence of vascular dysfunction, which may predispose the individual for other CVDs (and risk factors). Indeed, some studies show that microalbuminuria predicts new-onset hypertension as well as new-onset diabetes [9, 10].

8.4 Pathophysiology The glomerular filter is designed to retain macromolecules within the vascular compartment. In case of a defective filter, one may expect to find several different macromolecules in the urine. Given its size, albumin would pass through the filter. However, its negative charge appears to prevent it from freely passing. The actual barrier within the glomerular filter that prevents albumin from passing was recently redescribed [11]. Apparently, the vascular endothelium plays an important role, in particular, a negatively charged glycocalyx layer that not only covers the glomerular endothelium but also the endothelial layer on various vascular beds. In case of endothelial dysfunction and changes in the glycocalyx, albumin may pass more readily into the vascular wall in multiple vascular beds. This may be the missing link, explaining why leakage of albumin into the urine is associated with CVD [12]. Albumin leakage may just reflect endothelial dysfunction, the latter causing CVD and renal disease risk. Alternatively, leakage may directly cause vascular disease through low-grade inflammation in the vessel wall.

8.5 CVD Risk Prediction The predictive power of increased levels of albuminuria for renal disease risk are well described in patients with both type 1 and type 2 diabetes. Patients who develop microalbuminuria have marked increased risk of developing proteinuria and to progress to complete loss of kidney function. Mogensen wrote a seminal paper in 1984 describing the importance of microalbuminuria, not only as a renal-disease risk factor, but as a CVD risk factor in patients with diabetes [13]. It took some time until the importance of microalbuminuria as a CVD risk marker was further established (reviews [14, 15]). Although the risk for CVD in patients with type 1 diabetes is lower than in patients with type 2 diabetes, the CVD predictive effect of microalbuminuria is comparable for type 1 and type 2 diabetes [16]. Because of these findings, microalbuminuria was clearly linked to diabetes. The clinical applicability of microalbuminuria as a CVD risk predictor remained largely limited to diabetes, despite the fact that the Framingham study, established in 1984,


111

5

Alb< sex specific median

0 0

2

4

6

8

CVD event rate /1000py

CV endpoint rate / 1000 patient-years of follow-up

Years

Macro

b

PREVEND 548 n=40.5 48

4

5

Micro

3

Alb> sex specific median

Normo

2

CVD risk (%)

n=1568

Life Insurance data 1.3 million subjects (1925-1939)

1

a 10

Risk for CV mortality during follow-up (RR)

identified proteinuria as an important risk marker of (CVD) mortality in the general population [17]. It lasted 20 years before the predictive properties of microalbuminuria went beyond diabetes. Several important studies followed each other, such as the Multinational Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) project, the Prevention of Renal and Vascular Endstage Disease (PREVEND) study, the Nord-Trøndelag Health (HUNT) study, and the European Investigation into Cancer–Norfolk (EPIC–Norfolk) study [18–21]. They all showed that, as in diabetes, microalbuminuria is predictive for cardiovascular events, even in individuals without diabetes (Fig. 8.1a–d). In addition, these studies clearly illustrat-

2 138

10

100

1000 mg/l 167 mmHg

Baseline Albumin concentration Systolic blood pressure

c 60

n=8,206 Primary composite endpoint rate Adjusted composite endpoint rate*

50

Microalbuminuria

* Adjusted for ECG LV mass, Framingham Risk Score, and study treatment allocation

40 30 20 10 0

12.22 0.43 0.63 0.89 1.28 1.88 2.95 5.26 12.22 mg/mmol

type1 diabetes; n=161

80

type2 diabetes; n=266 total

60 40 20 0

1

2 3 4 Albuminuria quintile

5

d

Fig.8.1a–d Relationship between albuminuria and cardiovascular disease (CVD) risk: Panel a, healthy individuals, Framingham cohort. Reproduced from [22], with permission. Panel b, general population, Prevention of Renal and Vascular Endstage Disease (PREVEND) cohort. Panel c, hypertensive population, Losartan Intervention for Endpoint Reduction in Hypertension (LIFE) study. Reproduced from [23], with permission. Panel d, patients with diabetes. Panel b also shows the predictive power of systolic blood pressure for CVD risk before antihypertensive treatments were commercially available

112

8


ed that the definition of microalbuminuria is still arbitrary, as the relationship between urinary albumin and CVD risk is continuous, with no clear lower or upper limit [19, 24, 25]. In the hypertensive patient, microalbuminuria has been shown to be an important CVD risk factor (reviewed [26]). Larger cohort studies confirmed this to be independent from other risk markers in the general hypertensive population (MONICA) [27] and a hypertensive cohort with left-ventricular hypertrophy (LVH), the Losartan Intervention for Endpoint Reduction in Hypertension (LIFE) study [28]. Many (not all) guidelines recognize that the hypertensive patient with microalbuminuria is at increased CVD risk. Even in a mix of patients with increased CVD risk, such as the Heart Outcomes Prevention Evaluation (HOPE) study [29], microalbuminuria appears to be associated with increased CVD risk. In the above studies, microalbuminuria was associated and clustered with other well-known CVD risk factors (age, smoking, diabetes, hypertension, LVH, being overweight, metabolic syndrome, serum creatinine). The question is whether microalbuminuria is an independent risk predictor. Careful correction for such factors, and post-hoc selection of “healthy” individuals in large general population cohorts, revealed the marked and overwhelming independent predictive power of microalbuminuria. This was confirmed by the recent Framingham data that elegantly shows that in normotensive, nondiabetic individuals with normal renal function, microalbuminuria remains a strong predictor for CVD [22]. Glomerular filtration rate (GFR) has been described in multiple studies as a powerful predictor for CVD risk. The relationship between CVD risk and microalbuminuria could thus well be driven by low GFR. However, data from the Framingham and PREVEND studies show that microalbuminuria relates to CVD risk independently of the GFR level [22, 30, 31].

8.6 Targeting Albuminuria for CVD Risk Protection Clearly, microalbuminuria and proteinuria are independent predictors of CVD risk. Apart from risk stratification, to have any meaning in clinical practice, it must be shown that measures that reduce albuminuria or proteinuria are associated with cardiovascular protection. Several strategies are available to lower urinary albumin excretion in the microalbuminuric as well as in the proteinuric range. The albuminuria-lowering effect of antihypertensives, in particular, those that intervene in the renin-angiotensin-aldosterone system (RAAS), is well known. However, statins, glucosaminoglycans, and vitamin D analogues have proven to lower albuminuria [32–35]. Some of these strategies have showed cardioprotective characteristics in randomized controlled trials. However, few have been directed at albuminuria lowering per se to evaluate the effect on cardiovascular outcome. The Irbesartan Microalbuminuria Type 2 Diabetes Mellitus in Hypertensive Patients (IRMA-2) study, evaluating the effect of the angiotensin-II-antagonist irbesartan, shows that


113

albuminuria can be substantially lowered in microalbuminuric hypertensive type 2 diabetic patients, and this is associated with renal protection and some degree of cardiovascular protection [36]. However, this study was not powered to address the effect on cardiovascular events. The PREVEND Intervention Trial (PREVEND IT) study is the only randomized trial that studied the effect of albuminuria lowering in healthy microalbuminuric individuals (other CVD risk factors were excluded). The study showed that reducing albuminuria with the angiotensin-converting enzyme (ACE)-inhibitor fosinopril tended to be cardioprotective (Fig. 8.2a) [37]. A recent post-hoc analysis of the LIFE study found similar results in hypertensive patients: the more the losartan lowered albuminuria, the lower the cardiovascular event rate, irrespective of the effect of other CVD risk factors (Fig. 8.2b) [38]. A post-hoc analysis of the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) study showed that lowering albuminuria in patients

0.10

CV Morb/ mort (%)

n=800

Placebo

0.05

ACEi 30% albuminuria decrease vs placebo (month 3)

0

0

10

20

a

30

40

Fraction free of CV disease

Months

1.00 0.95

L o w UA C R 0 – L o w U A C R 1 L o w U A C R 0 – H igh UAC R1

0.90

H i g h U A C R 0 – L o w UA C R 1

0.85

High UACR0 – High UACR1

0.80 12

24

36

48

60

Months

b CV Endpoint

% with CV endpoint

40

30% albuminuria decrease Month 3 vs baseline

10

0 0

c

12

24

Month

36

48

Fig. 8.2a–c Cardiovascular protection using therapies that lower albuminuria in different populations: Panel a, individuals from the general population: Prevention of Renal and Vascular Endstage Disease Intervention Trial (PREVEND IT); angiotensinconverting enzyme (ACE) inhibitor versus placebo. Panel b, hypertensive population: Losartan Intervention for Endpoint Reduction in Hypertension (LIFE) trial. Reproduced from [23], with permission. Angiotensin receptor blocker (ARB) versus beta blocker. Panel c, patients with type 2 diabetes: Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) trial; ARB versus placebo. UACR0 urinary albumin creatinine ratio at baseline, UACR1 urinary albumin creatinine ratio at year 1


114

8

with nephritic-range albuminuria is also associated with cardiovascular protection (Fig. 8.2c) [38]. Future CVD trials involving drugs that target albuminuria more specifically are needed to resolve the issue of whether specific lowering of albuminuria results in cardiovascular protection and whether this is a cost-effective healthcare approach. Screening, specific targeting, and monitoring of increased urinary albumin levels may have distinct public-health implications in relation to CVD prevention [39].

References 1.

2. 3. 4. 5.

6. 7.

8. 9. 10.

11. 12. 13. 14.

15. 16.

Levey AS, Eckardt KU, Tsukamoto Y et al (2005) Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 67:2089–2100 Zandi-Nejad K, Eddy AA, Glassock RJ et al (2004) Why is proteinuria an ominous biomarker of progressive kidney disease? Kidney Int Suppl 92:S76–89 Bakker SJ, Gansevoort RT, de Zeeuw D (2009) Albuminuria: what can we expect from the determination of nonimmunoreactive albumin? Curr Hypertens Rep 11:111–117. Witte EC, Lambers Heerspink HJ, de Zeeuw D et al. (2009) First morning voids are more reliable than spot urine samples to assess microalbuminuria. J Am Soc Nephrol. 20:436–443 Lambers Heerspink HJ, Brantsma AH, de Zeeuw D et al (2008) Albuminuria assessed from first-morning-void urine samples versus 24-hour urine collections as a predictor of cardiovascular morbidity and mortality. Am J Epidemiol 168:897–905 Brinkman JW, de Zeeuw D, Gansevoort RT (2007) Prolonged frozen storage of urine reduces the value of albuminuria for mortality prediction. Clin Chem. 53:153–154 Lambers Heerspink HJ, Nauta FL, Van der Zee C et al (2009) Alkalinization of urine samples preserves albumin concentrations during prolonged frozen storage in patients with diabetes mellitus. Diabet Med 26:556–559 de Zeeuw D, Parving HH, Henning RH (2006) Microalbuminuria as an early marker for cardiovascular disease. J Am Soc Nephrol 17:2100–2105 Brantsma AH, Bakker SJ, de Zeeuw D (2006) Urinary albumin excretion as a predictor of the development of hypertension in the general population. J Am Soc Nephrol 17:331–335 Brantsma AH, Bakker SJ, Hillege HL et al (2005) Urinary albumin excretion and its relation with C-reactive protein and the metabolic syndrome in the prediction of type 2 diabetes. Diabetes Care 28:2525–2530 Haraldsson B, Nystrom J, Deen WM (2008) Properties of the glomerular barrier and mechanisms of proteinuria. Physiol Rev 88:451–487 Satchell SC, Tooke JE (2008) What is the mechanism of microalbuminuria in diabetes: a role for the glomerular endothelium? Diabetologia 51(5):714–725 Mogensen CE (1984) Microalbuminuria predicts clinical proteinuria and early mortality in maturity-onset diabetes. N Engl J Med 310:356–360 Dinneen SF, Gerstein HC (1997) The association of microalbuminuria and mortality in noninsulin-dependent diabetes mellitus. A systematic overview of the literature. Arch Intern Med 157:1413–1418 Weir MR (2004) Microalbuminuria in type 2 diabetes: an important, overlooked cardiovascular risk factor. J Clin Hypertens 6:134–143 Yuyun MF, Dinneen SF, Edwards OM et al (2003) Absolute level and rate of change of albuminuria over 1 year independently predict mortality and cardiovascular events in patients with diabetic nephropathy. Diabet Med 20:277–282


17. 18.

19. 20.

21.

22.

23.

24.

25. 26. 27. 28. 29. 30.

31. 32.

33.

34.

35. 36.

115

Kannel WB, Stampfer MJ (1984) The prognostic significance of proteinuria: the Framingham Study. Am Heart J 108:1347–1352 Borch-Johnsen K, Feldt-Rasmussen B, Strandgaard S et al (1999) Urinary albumin excretion. An independent predictor of ischemic heart disease. Arterioscler Thromb Vasc Biol 19:1992–1997 Hillege HL, Fidler V Diercks GFH et al (2002) Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in the general population. Circulation 106:1777–1782 Romundstad S, Holmen J, Kvenild K et al (2003) Microalbuminuria and all-cause mortality in 2,089 apparently healthy individuals: a 4.4-year follow-up study. The Nord-Trøndelag Health Study (HUNT), Norway. Am J Kidney Dis 42:466–473 Yuyun MF, Khaw KT Luben R et al (2004) Microalbuminuria independently predicts all-cause and cardiovascular mortality in a British population: The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) population study. Int J Epidemiol 33:189–198 Arnlov J, Evans JC, Meigs JB (2005) Low-grade albuminuria and incidence of cardiovascular disease events in nonhypertensive and nondiabetic individuals: the Framingham Heart Study. Circulation 112:969–975 Olsen MH, Wachtell K, Ibsen H et al (2006) Reductions in albuminuria and in electrocardiographic left ventricular hypertrophy independently improve prognosis in hypertension: The LIFE Study. J Hypertension 24:775–781 Klausen K, Borch-Johnsen K, Jensen G et al (2004) Very low levels of microalbuminuria are associated with increased risk of coronary heart disease and death independently of renal function, hypertension, and diabetes. Circulation 110:32–35 Ratto E, Leoncini G, Viazzi F et al (2006) Microalbuminuria and cardiovascular risk assessment in primary hypertension: should threshold levels be revised? Am J Hypertens. 19:728–734 Bigazzi R, Bianchi S, Baldari D et al (1998) Microalbuminuria predicts cardiovascular events and renal insufficiency in patients with essential hypertension. J Hypertens 16:1325–1333 Jensen JS, Feldt-Rasmussen B, Strandgaard S (2000) Arterial hypertension, micro-albuminuria, and risk of ischemic heart disease. Hypertension 35:898–903 Wachtell K, Ibsen H Olsen MH et al (2003) Albuminuria and cardiovascular risk in hypertensive patients with left ventricular hypertrophy: the LIFE study. Ann Intern Med 139:901–906 Gerstein HC, Mann JF, Yi Q et al (2001) Albuminuria and risk of cardiovascular events, death, and heart failure in diabetic and nondiabetic individuals. JAMA 286:421–426 Brantsma AH, Bakker SJ, Hillege HL et al (2008) Cardiovascular and renal outcome in subjects with K/DOQI stage 1–3 chronic kidney disease: the importance of urinary albumin excretion. Nephrol Dial Transplant. 2008 23:3851–3858 Ninomiya T, Perkovic V, de Galan BE et al (2009) Albuminuria and kidney function independently predict cardiovascular and renal outcomes in diabetes. J Am Soc Nephrol 20:1813–1821 Tonolo G, Ciccarese M, Brizzi P et al (1997). Reduction of albumin excretion rate in normotensive microalbuminuric type 2 diabetic patients during long-term simvastatin treatment. Diabetes Care 20:1891–1895 Nakamura T, Ushiyama C, Hirokawa K et al (2002) Effect of cerivastatin on urinary albumin excretion and plasma endothelin-1 concentrations in type 2 diabetes patients with microalbuminuria and dyslipidemia. Am J Nephrol 21:449–454 Gambaro G, Kinalska I, Oksa A et al (2002) Oral sulodexide reduces albuminuria in microalbuminuric and macroalbuminuric type 1 and type 2 diabetic patients: the Di.N.A.S. randomized trial. J Am Soc Nephrol 13:1615–1625 Agarwal R, Acharya M, Tian J et al (2005) Antiproteinuric effect of oral paricalcitol in chronic kidney disease. Kidney Int. 68:2823–2828 Parving HH, Lehnert H, Brochner-Mortensen J et al (2001) The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes. N Engl J Med 345:870–878

8

116


37.

Asselbergs FW, Diercks GFH, Hillege H et al (2004) Effects of fosinopril and pravastatin on cardiovascular events in subjects with microalbuminuria. Circulation 110:2809–2816 de Zeeuw D, Remuzzi G, Parving HH et al (2004) Albuminuria, a therapeutic target for cardiovascular protection in type 2 diabetic patients with nephropathy. Circulation 110(8):921–927 de Jong PE, Curhan G (2006) Screening, monitoring and treatment of albuminuria – public health perspectives. J Am Soc Nephrol 17(8):2120–2126

38. 39.

Microalbuminuria and Kidney Disease: An Evidence-based Perspective

9

R.G. Kalaitzidis, P. Dalal, G.L. Bakris

Abstract In the early 1960s, microalbuminuria was noted as a predictor of nephropathy and higher cardiovascular risk in patients with type 1 diabetes mellitus. Over the past four decades, however, the epidemiological evidence has become far stronger, implicating it as a cardiovascular risk marker than a risk factor associated with nephropathy. Microalbuminuria is also a marker of endothelial dysfunction, increased vascular leakage of albumin, and a marker of inflammation. In this context, it is also a marker for risk of developing hypertension and making it more difficult to control blood pressure if hypertension is already present. This chapter reviews the role of microalbuminuria as a marker of cardiovascular risk and nephropathy identifier. It also reviews the association of microalbuminuria with other cardiovascular risk factors and the pathophysiological association between microalbuminuria and vascular damage. In addition, the chapter reviews trial data that evaluated microalbuminuria for its prognostic significance on cardiovascular outcomes, as well as existing therapeutic interventions for reducing urinary albumin excretion in patients with high cardiovascular risk. Keywords: Microalbuminuria • Kidney disease • Cardiovascular risk • Hypertension • Endothelial dysfunction

9.1 Introduction More than 70 million Americans suffer from some form of cardiovascular (CV) disease, the single leading cause of mortality in both men and women, causing more than 850,000 deaths every year in the USA [1]. Microalbuminuria (MA) is a wellrecognized predictor of CV disease morbidity and mortality in patients with or without diabetes [2–4]. Whereas early research focused on the relevance of MA as a risk factor, i.e., directly relating to the pathophysiology of the mechanism for kidney disease progression, data over the past decade has focused on its role as a predictor of

G.L. Bakris () Department of Medicine, Hypertensive Diseases Unit, The University of Chicago Pritzker School of Medicine, Chicago, IL, USA Cardiorenal Syndrome. Adel E. Berbari, Giuseppe Mancia (Eds.) © Springer-Verlag Italia 2010

117

R. G. Kalaitzidis et al.

118

9

CV disease [5]. As will be seen in this chapter, MA is a risk marker, i.e., it does not contribute to the pathophysiology of disease but is, rather, an indicator of underlying vascular inflammation. The proposed mechanisms primarily involve local injury to the vascular smooth muscle and endothelial cells through oxidative stress and subsequent changes in nitric oxide. These changes in vascular integrity are associated with an increase in a variety of proinflammatory cytokines, culminating in cell proliferation and increase in vascular permeability.

9.2 Definition of Microalbuminuria According to the current definition, the term MA refers to urinary albumin excretion (UAE) of >30 mg/day and in the range of 20–200 mg/min (30–299 mg/day) [6]. Evidence from epidemiological studies suggest that UAE should be viewed as a continuum of risk for CV diseases, with the lower the UAE the lesser the CV disease risk [7]. There are three methods of collecting and measuring urinary albumin: (a) measuring albumin concentration or albumin creatinine ratio (UACR) in a random spot urine specimen; (b) measuring albumin concentration and simultaneously measuring creatinine clearance in a 24-h urinary collection; (c) measuring albumin levels in a timed urinary collection (e.g., overnight or over 4 h). Spot collection of morning urine requires knowledge of the factors that affect UACR measurement [8], (Table 9.1). UAE range is 25% lower during sleep than when awake. Furthermore, MA can vary daily from 40% to 100%. These largely biological variations are due to inflammation associated with a variety of factors ranging from high lipid or sodium ingestion to infections or underlying worsening of atherosclerosis. The American Diabetes Association recommends that at least two morning urine specimens collected within 3 months should be abnormal to consider patients as having MA [8]. Point of care testing is now available using a spot urine to assess presence and magnitude of MA and is used in screening programs around the world [9, 10].

Table 9.1 Factors that affect measurement of urine albumin and creatinine Albumin excretion

Creatinine excretion

Blood pressure

Muscle mass

Salt intake

Race

Volume status

Gender

Fasting versus nonfasting sample Time of day

9 Microalbuminuria and Kidney Disease: An Evidence-based Perspective

119

9.3 Prevalence of Microalbuminuria MA occurs in 30% of middle-aged individuals with type 1 or 2 diabetes and in 10–15% of individuals without diabetes [11]. Variations in prevalence are primarily due to patient selection or factors that affect albumin excretion (Table 9.2).

Table 9.2 Factors known to influence the development of microalbuminuria Elevated blood pressure (systolic, diastolic, mean) Increased body mass index Insulin resistance (hyperinsulinemia) Endothelial dysfunction Decrease in high density lipoprotein levels Smoking Salt sensitivity Increased age DD-ACE genotype

9.4 Pathophysiology of Microalbuminuria MA is more a marker than a pathogenic factor to the atherosclerotic process. There are several proposed hypotheses connecting MA to increase CV disease risk. All patients with MA have an elevated transcapillary escape rate of albumin. MA is more likely to be present if the patient has known CV disease risk factors, such as hypertension, hyperlipidemia, insulin resistance, and obesity. Inflammation markers, such as high-sensitivity C-reactive protein (hs-CRP), fibrinogen, interleukin 6 (IL-6); and indicators of procoagulatory state, such as von Willebrand factor (vWF), are usually elevated if MA is present [3, 12]. Whereas the fundamental mechanisms of vascular injury leading to MA are similar between individuals with and without diabetes, there are some differences. In patients without diabetes, generalized vascular leakiness is caused by alterations in defects in barrier membranes. These alterations are largely triggered by increased microvascular pressure, which leads to injury to the endothelium [12]. The resultant defect in endothelial permeability permits lipid influx into the vessel wall, contributing to atherosclerotic changes. Many other acute and chronic illnesses that mediate immune responses, including complement activation, macrophages, neutrophils, and endothelial stimulation, all contribute to this diverse inflammatory injury [12] (Fig. 9.1). In individuals with diabetes, albumin is glycated and associated with generation of

120


9

Fig. 9.1 Factors in the pathogenesis of increased endothelial permeability. AGE, advanced glycation end products; HTN, hypertension; LDL, low-density lipoprotein; NAD+, nicotinamide adenine dinucleotide; NADPH, nicotinamide adenine dinucleotide phosphate, reduced; RAGE, receptor for AGE

reactive oxygen species (ROS). In addition, many other factors, such as advanced glycation end products, ROS, and other cellular toxins contribute to vascular injury. Once such injury occurs, the effects of pressor hormones, such as angiotensin II, are magnified, resulting in faster progression of vascular injury. The end result is direct injury to epithelial cells of the glomerular membrane, vascular smooth muscle cells, and the podocyte basement membrane.

9.5 Cardiovascular Risk 9.5.1 Hypertension Patients with hypertension are more likely to have MA than those with normal blood pressure. Likewise, people with MA are at greater risk for developing hypertension. The Nurses’ Health Study showed an independent association between the level of urinary albumin and the development of hypertension in individuals who did not have diabetes or hypertension. This association between albuminuria level and risk of

9 Microalbuminuria and Kidney Disease: An Evidence-based Perspective

121

hypertension extended into the high normal range, i.e., 300 mg/day, predict kidney failure [33], MA is not a marker of kidney disease but of worsening endothelial dysfunction. Increases in MA over time despite good systolic blood pressure control, i.e., 300 mg/day of urinary protein, clearly have kidney disease and are at high risk to progress to end-stage renal disease. Moreover, the magnitude of proteinuria is a predictor of kidney disease progression [35]. This concept is further supported by a cross-sectional study that evaluated the risk of kidney disease progression in the presence and absence of albuminuria in more than 4,400 people [36]. This study showed that albuminuria levels >200 mg/day were highly predictive of kidney disease progression, whereas glomerular filtration rate (GFR) levels were more predictive of CV disease risk. It is important to note that all clinical outcome trials of nephropathy progression, positive for some therapeutic intervention, recruited patients with proteinuria >300 mg/day [37] (Table 9.3). Moreover, all trials in which patients showed the slowest nephropathy progression demonstrated a >30% reduction in proteinuria, usually with RAS blockers [38, 39] (Table 9.4). Thus, whereas the presence of MA is not indicative of kidney disease, its increase in the presence of blood pressure control treatment is a poor prognostic sign relative to kidney disease progression. Therefore, monitoring this laboratory marker should occur once or twice annually [40].


126

9

Table 9.3 Summary of long-term (≥3 years) outcome trials focused on progression to end-stage renal disease in people with advanced nephropathy Patients without diabetes

Patients with diabetes

MDRD [41]

Captopril Trial [42]

AIPRI [43]

Bakris GL [44]

REIN [45]

IDNT [46]

AASK [47]

RENAAL [48]

REIN-2 [49] Hou et al [51]

ABCD [50]a

AASK, African American Study of Kidney Disease; ABCD, Appropriate Blood Pressure Control in Diabetes; AIPRI, Angiotensin-Converting Enzyme Inhibition in Progressive Renal Insufficiency Study; IDNT, Irbesartan in Diabetic Nephropathy Trial; MDRD, Modification of Diet in Renal Disease; REIN, Ramipril Efficacy In Nephropathy; RENAAL, Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan aOnly the ABCD trial was negative for the primary outcome but had a cohort of patients with normoalbuminuria or microalbuminuria and glomerular filtration rates (GFR) >80 ml/min at baseline. All other studies had proteinuria >300 mg/day at baseline and GFR values well below 50 ml/min

Table 9.4 Summary of long-term outcome trials focused on proteinuria reduction in relation to advanced nephropathy progression Increased time to dialysis (30-35% proteinuria reduction)

No change in time to dialysis (no proteinuria reduction)

Captopril [42]

DHPCCB arm–IDNT [46]

AASK [52]

DHPCCB arm–AASK [52]

RENAAL [48] IDNT [46] AASK, African American Study of Kidney Disease; DHPCCB, dihydropyridine calcium channel blocker; IDNT, Irbesartan in Diabetic Nephropathy Trial; RENAAL, Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan

9.8 Therapeutic Intervention and Cardiorenal Disease Risk Reduction The same factors that reduce the risk of nephropathy and CV disease also reduce the risk of developing MA, or if MA is already present, will increase the likelihood of normalization. Specifically, lifestyle modifications, including 30 kg/m2

Central obesity

Fasting glucose ≥100 mg/dl

Type 2 diabetes, fasting glucose ≥100 mg/dl or insulin resistance (fasting insulin in top 25% of nondiabetic population)

Three of the following five criteria

NCEP Adult Treatment Panel III [2, 3]

Glucose

Diagnostic criteria Glucose criteria plus two additional criteria

World Health Organization [4, 5]

Table 10.1 Definitions of the cardiometabolic syndrome

Not applicable